Accelerating Real-Time Shading with Reverse Reprojection ...jdl/papers/reproj/nehab_gh07_slides.pdf · Accelerating Real-Time Shading with Reverse Reprojection Caching Diego Nehab1

Accelerating Real-Time Shading withReverse Reprojection Caching

Diego Nehab1 Pedro V. Sander2 Jason Lawrence3

Natalya Tatarchuk4 John R. Isidoro4

1Princeton University2Hong Kong University of Science and Technology

3University of Virginia

4Advanced Micro Devices, Inc.

Motivation

Motivation

Previous work

• Dedicated hardware

• Address Recalculation Pipeline [Regan and Pose 1994]

• Talisman [Torborg and Kajiya 1996]

• Image based rendering

• Image Warping [McMillan and Bishop 1995]

• Post Rendering 3D Warp [Mark et al. 1997]

Previous work

• Interactivity for expensive renderers

• Frameless rendering [Bishop et al. 1994]

• Render Cache [Walter et al. 1999]

• Holodeck/Tapestry [Simmons et al. 1999/2000]

• Corrective Texturing [Stamminger et al 2000]

• Shading Cache [Tole et al. 2002]

Our approach

• Explore coherence in real-time rendering

RecomputeRecompute

Our approach

• Explore coherence in real-time rendering

LookupLookup Hit?Hit?

Load/ReuseLoad/Reuse

RecomputeRecompute

UpdateUpdate

Requirements

• Load/reuse path must be cheaper

• Cache hit ratio must be high

• Lookup/update must be efficient

LookupLookup Hit?Hit?

Load/ReuseLoad/Reuse

RecomputeRecompute

UpdateUpdate

First insight

• Cache only visible surface fragments

• Use screen space buffer to store cache

• Output sensitive memory

• Keep everything in GPU memory

• Leverage hardware Z-buffering for eviction

Cache hit ratio

Cache hit ratio results

[Walter et al. 1999]

Second insight

• Use reverse mapping

• Recompute scene geometry at each frame

• Leverage hardware filtering for lookup

Third insight

• Do not need to reproject at the pixel level

• Hard work is performed at the vertex level

Address calculation

Time t Time t+1

Hit or miss?

Time t Time t+1

Hit or miss?

cached depth

Time t

• Load cached depth

• Compare withexpected depth

expected depth

Third insight

• Do not need to reproject at the pixel level

• Hard work is performed at the vertex level

• Pass old vertex coords as texture coords

• Leverage perspective-correct interpolation

• One single final division within pixel shader

What to cache?

• Slow varying, expensive computations

• procedural albedo

• Values required in multiple passes

• color in depth of field or motion blur

• Samples within a sampling process

• amortized shadow map tests

Refreshing the cache

• Cached entries become stale with time• View dependent effects, repeated resampling

• Implicit (multipass algorithms)• Flush entire cache each time step

• Random updates• Refresh random fraction of pixels

• Amortized update• Combine cache with new values at each frame

Motion blur

60fps brute force

3 passes

Reuse albedo in multipass

• For each time step

• Fully compute albedo in first pass

• For each remaining pass

• Lookup into first pass and try to reuse

Motion blur

60fps brute force

3 passes

Motion blur

60fps cached30fps brute force

6 passes

Motion blur

30fps cached14 passes

Randomly distributed refresh

1/4th updated

Error plot

Amortized super-sampling

• Cache updated by recursive filter rule

• Lambda controls variance reduction...

• ...but also the lifespan

Trade-offs

VarianceLifespan

Variance reduction at work

4 tap PCF16 tap PCF

Reusing shadow map tests

• At each frame, perform new shadow tests

• Read running sum from cache

• Blend the two values

• Update cache and display results

Variance reduction at work

4 tap PCF16 tap PCF

Variance reduction at work

16 tap PCF 4 tap amortized

Conclusions

• Shading every frame anew is wasteful

• We can reuse some of the shadingcomputations from previous frames

• Use reverse reprojection caching to do thatin real-time rendering applications

• Less work per frame = faster rendering

Future work

• Track surface points and select shaderlevel of detail based on screenspace speed

• Change refresh rate per pixel based onrate of cached value change

• Use code analysis to automatically selectappropriate values to cache